Active stocks on Octuber

Abstract

Active stocks of most popular companies were analyzed in the period from Octuber 1 to Octuber 25, 2021.

Resources

• Webscrapping data from Yahoo Finance.
• pandas for data analysis.
• plotly for data visualization.

Modules

import time
import datetime
import pandas as pd
import plotly.express as px

Dataset: webscrapping from Yahoo Finance

Financial variables: Date, Open, High, Low, Close (close price adjusted for splits), Adj Close (Adjusted close price adjusted for splits and dividend and/or capital gain distributions), Volume. Currency in USD.

Set the company of interest in the ticker variable.

# Set the parameters to dowload Yahoo Finance data
# Yahoo Finance: historical prices from selected company

# Set the company of interes:
ticker = 'TSLA'

# Convert string to mktime
period1 = int(time.mktime(datetime.datetime.strptime("01/01/2021", "%d/%m/%Y").timetuple()))
period2 = int(time.mktime(datetime.datetime.strptime("25/10/2021", "%d/%m/%Y").timetuple()))
interval = '1d'

# Read data from web and create DataFrame
query_string = f'https://query1.finance.yahoo.com/v7/finance/download/{ticker}?period1={period1}&period2={period2}&interval={interval}&events=history&includeAdjustedClose=true'
df = pd.read_csv(query_string)

# Output data into CSV
df.to_csv('./YahooFinances_TSLA.csv')

Data Analysis

df = pd.read_csv('./Stocks_Companies_YahooFinance.csv', header = 0)

Table 1. Stocks of popular companies.

df.head(10)

	Company	Date	Close	Adj Close	Volume	Daily Return	% Daily Return
0	AAPL	10/1/2021	142.65	142.65	94639600	0.01	0.81
1	AAPL	10/4/2021	139.14	139.14	98322000	-0.02	-2.49
2	AAPL	10/5/2021	141.11	141.11	80861100	0.01	1.41
3	AAPL	10/6/2021	142.00	142.00	83221100	0.01	0.63
4	AAPL	10/7/2021	143.29	143.29	61732700	0.01	0.90
5	AAPL	10/8/2021	142.90	142.90	58718700	0.00	-0.27
6	AAPL	10/11/2021	142.81	142.81	64452200	0.00	-0.06
7	AAPL	10/12/2021	141.51	141.51	73035900	-0.01	-0.91
8	AAPL	10/13/2021	140.91	140.91	78762700	0.00	-0.42
9	AAPL	10/14/2021	143.76	143.76	69907100	0.02	2.00

Adj Close vs Volume

px.scatter(data_frame = df,
           x = 'Adj Close',
           y= 'Volume',
           size = 'Volume',
           color = 'Company',
           title = 'Volume vs Adj Close',
           # Scales
           range_x = [-500, 4000],
           range_y = [-20e+06, 15e+07],          
           # Company when hover over points
           hover_name = 'Company',
           text = "Company",
           # Animation based on date
           animation_frame = 'Date',
           size_max = 100)

Figure 1. Animated pairplot of popular companies: Adj Close vs Volume. Circle size based on Volume. Color key for different companies.

Link to image: https://plotly.com/~melisadigiacomo/1/

Daily Return vs Volume

px.scatter(data_frame = df,
           x = 'Volume',
           y= '% Daily Return',
           size = 'Volume',
           color = 'Company',
           title = '% Daily Return vs Volume',
           # Scale
           range_y = [-15,20],
           range_x = [-20e+06, 12e+07], 
           # Company when hover over points
           hover_name = 'Company',
           text = "Company",
           # Animation based on date
           animation_frame = 'Date',
           size_max = 100)

Figure 2. Animated pairplot of popular companies: % Daily Return vs Volume. % Daily Return is the percentage of the natural log of daily Adj Close ratio. Circle size based on Volume. Color key for different companies.

Link to image: https://plotly.com/~melisadigiacomo/3/

Tesla, Inc.

Table 2. Stocks of Tesla, Inc.

data_TSLA = df.where(df.Company == 'TSLA').dropna()
data_TSLA.head(10)

	Company	Date	Close	Adj Close	Volume	Daily Return	% Daily Return
119	TSLA	10/1/2021	775.22	775.22	17031400.0	0.00	-0.03
120	TSLA	10/4/2021	781.53	781.53	30483300.0	0.01	0.81
121	TSLA	10/5/2021	780.59	780.59	18432600.0	0.00	-0.12
122	TSLA	10/6/2021	782.75	782.75	14632800.0	0.00	0.28
123	TSLA	10/7/2021	793.61	793.61	19195800.0	0.01	1.38
124	TSLA	10/8/2021	785.49	785.49	16711100.0	-0.01	-1.03
125	TSLA	10/11/2021	791.94	791.94	14200300.0	0.01	0.82
126	TSLA	10/12/2021	805.72	805.72	22020000.0	0.02	1.73
127	TSLA	10/13/2021	811.08	811.08	14120100.0	0.01	0.66
128	TSLA	10/14/2021	818.32	818.32	12247200.0	0.01	0.89

Table 3. Descriptive statistics from each variable.

data_TSLA.describe()

	Close	Adj Close	Volume	Daily Return	% Daily Return
count	17.000000	17.000000	1.700000e+01	17.000000	17.000000
mean	835.176471	835.176471	2.180491e+07	0.016471	1.641176
std	65.219055	65.219055	1.192739e+07	0.029568	2.931778
min	775.220000	775.220000	1.224720e+07	-0.010000	-1.030000
25%	785.490000	785.490000	1.463280e+07	0.000000	0.180000
50%	811.080000	811.080000	1.843260e+07	0.010000	0.820000
75%	865.800000	865.800000	2.283680e+07	0.020000	1.740000
max	1024.860000	1024.860000	6.285210e+07	0.120000	11.920000

px.scatter(data_frame = data_TSLA,
           x = 'Date',
           y= 'Volume',
           size = 'Volume',
           color = '% Daily Return',
           title = 'TSLA: Date vs Volume - Octuber',
           # Company when hover over points
           hover_name = 'Company',
           text = '% Daily Return',
           color_continuous_scale = 'sunset',
           size_max = 100)

Figure 3. Pairplot: % Daily Return vs Volume of Tesla, Inc. % Daily Return is the percentage of the natural log of daily Adj Close ratio. Circle size based on Volume and text inside indicates % Daily Return. Color key for % Daily Return.

Link to image: https://plotly.com/~melisadigiacomo/5/

Tesla, Inc. showed a drastic shift on Octuber 25th, 2021, both on volume and % Daily Return.

Let's analyzed what happened with the other companies on that date.

Table 4. Stocks of popular companies on October 25, 2021.

df_25 = df.where(df.Date == '10/25/2021').dropna()
df_25.head(10)

	Company	Date	Close	Adj Close	Volume	Daily Return	% Daily Return
16	AAPL	10/25/2021	148.64	148.64	50720600.0	0.00	-0.03
33	AMZN	10/25/2021	3320.37	3320.37	2226000.0	0.00	-0.46
50	FB	10/25/2021	328.69	328.69	38409000.0	0.01	1.25
67	GOOG	10/25/2021	2775.46	2775.46	1054100.0	0.00	0.11
84	KO	10/25/2021	54.23	54.23	11855000.0	0.00	-0.40
101	MCD	10/25/2021	237.34	237.34	3178400.0	0.00	-0.46
118	NFLX	10/25/2021	671.66	671.66	3833500.0	0.01	1.03
135	TSLA	10/25/2021	1024.86	1024.86	62852100.0	0.12	11.92

px.scatter(data_frame = df_25,
           x = 'Volume',
           y= '% Daily Return',
           size = 'Volume',
           color = 'Company',
           title = 'Volume vs % Daily Return - Octuber 25, 2021',
           # Company when hover over points
           hover_name = 'Company',
           text = "Company",
           size_max = 100)

Figure 4. Pairplot: Volume vs % Daily Return of popular companies on Octuber 25, 2021. % Daily Return is the percentage of the natural log of daily Adj Close ratio. Circle size based on Volume. Color key for different companies.

Link to image: https://plotly.com/~melisadigiacomo/7/

px.scatter(data_frame = df_25,
           x = 'Company',
           y= 'Volume',
           size = 'Volume',
           color = '% Daily Return',
           title = 'Company vs Volume - Octuber 25, 2021',
           # Company when hover over points
           hover_name = 'Company',
           text = '% Daily Return',
           color_continuous_scale = 'sunset',
           size_max = 100)

Figure 5. Pairplot: Company vs Volume on Octuber 25, 2021. % Daily Return is the percentage of the natural log of daily Adj Close ratio. Circle size based on Volume and text inside indicates % Daily Return. Color key for % Daily Return.

Link to image: https://plotly.com/~melisadigiacomo/9/